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[MICCAI'21] [Tensorflow] Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network

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MICCAI2021 RVGAN

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This code is for our paper "RV-GAN: Segmenting Retinal Vascular Structure inFundus Photographs using a Novel Multi-scaleGenerative Adversarial Network" which is part of the supplementary materials for MICCAI 2021 conference. The paper has since been accpeted to MICCAI 2021 and will be presented in September 2021.

Arxiv Pre-print

https://arxiv.org/pdf/2101.00535v2.pdf

Citation

@article{kamran2021rv,
  title={RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network},
  author={Kamran, Sharif Amit and Hossain, Khondker Fariha and Tavakkoli, Alireza and Zuckerbrod, Stewart Lee and Sanders, Kenton M and Baker, Salah A},
  journal={arXiv preprint arXiv:2101.00535v2}, 
  year={2021}
}

Pre-requisite

  • Ubuntu 18.04 / Windows 7 or later
  • NVIDIA Graphics card

Installation Instruction for Ubuntu

sudo apt-get install pip3 python3-dev
  • Install Tensorflow-Gpu version-2.0.0 and Keras version-2.3.1
sudo pip3 install tensorflow-gpu==2.0.3
sudo pip3 install keras==2.3.1
  • Install packages from requirements.txt
sudo pip3 install -r requirements.txt

Dataset Pre-processing

  • Type this in terminal to run the strided_crop_DRIVE.py, strided_crop_STARE.py or strided_crop_CHASE.py file.
python3 strided_crop_DRIVE.py --input_dim=128 --stride=32
  • There are different flags to choose from. Not all of them are mandatory.
    '--input_dim', type=int, default=128
    '--stride', type=int, default=32

NPZ file conversion

  • Convert all the images to npz format using convert_npz_DRIVE.py, convert_npz_STARE.py or convert_npz_CHASE.py file.
python3 convert_npz_DRIVE.py --input_dim=(128,128) --n_crops=210 --outfile_name='DRIVE'
  • There are different flags to choose from. Not all of them are mandatory.
    '--input_dim', type=int, default=(128,128)
    '--n_crops', type=int, default=210
    '--outfile_name', type=str, default='DRIVE'

Training

  • Type this in terminal to run the train.py file
python3 train.py --npz_file=DRIVE --batch=4 --epochs=200 --savedir=RVGAN
  • There are different flags to choose from. Not all of them are mandatory
   '--npz_file', type=str, default='DRIVE', help='path/to/npz/file'
   '--batch_size', type=int, default=4
   '--input_dim', type=int, default=128
   '--epochs', type=int, default=200
   '--savedir', type=str, required=False, help='path/to/save_directory',default='RVGAN'

License

The code is released under the BSD 3-Clause License, you can read the license file included in the repository for details.

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